-0.000 282 006 284 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 006 284(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
-0.000 282 006 284(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-0.000 282 006 284| = 0.000 282 006 284


2. First, convert to binary (in base 2) the integer part: 0.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 0 ÷ 2 = 0 + 0;

3. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.000 282 006 284.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.000 282 006 284 × 2 = 0 + 0.000 564 012 568;
  • 2) 0.000 564 012 568 × 2 = 0 + 0.001 128 025 136;
  • 3) 0.001 128 025 136 × 2 = 0 + 0.002 256 050 272;
  • 4) 0.002 256 050 272 × 2 = 0 + 0.004 512 100 544;
  • 5) 0.004 512 100 544 × 2 = 0 + 0.009 024 201 088;
  • 6) 0.009 024 201 088 × 2 = 0 + 0.018 048 402 176;
  • 7) 0.018 048 402 176 × 2 = 0 + 0.036 096 804 352;
  • 8) 0.036 096 804 352 × 2 = 0 + 0.072 193 608 704;
  • 9) 0.072 193 608 704 × 2 = 0 + 0.144 387 217 408;
  • 10) 0.144 387 217 408 × 2 = 0 + 0.288 774 434 816;
  • 11) 0.288 774 434 816 × 2 = 0 + 0.577 548 869 632;
  • 12) 0.577 548 869 632 × 2 = 1 + 0.155 097 739 264;
  • 13) 0.155 097 739 264 × 2 = 0 + 0.310 195 478 528;
  • 14) 0.310 195 478 528 × 2 = 0 + 0.620 390 957 056;
  • 15) 0.620 390 957 056 × 2 = 1 + 0.240 781 914 112;
  • 16) 0.240 781 914 112 × 2 = 0 + 0.481 563 828 224;
  • 17) 0.481 563 828 224 × 2 = 0 + 0.963 127 656 448;
  • 18) 0.963 127 656 448 × 2 = 1 + 0.926 255 312 896;
  • 19) 0.926 255 312 896 × 2 = 1 + 0.852 510 625 792;
  • 20) 0.852 510 625 792 × 2 = 1 + 0.705 021 251 584;
  • 21) 0.705 021 251 584 × 2 = 1 + 0.410 042 503 168;
  • 22) 0.410 042 503 168 × 2 = 0 + 0.820 085 006 336;
  • 23) 0.820 085 006 336 × 2 = 1 + 0.640 170 012 672;
  • 24) 0.640 170 012 672 × 2 = 1 + 0.280 340 025 344;
  • 25) 0.280 340 025 344 × 2 = 0 + 0.560 680 050 688;
  • 26) 0.560 680 050 688 × 2 = 1 + 0.121 360 101 376;
  • 27) 0.121 360 101 376 × 2 = 0 + 0.242 720 202 752;
  • 28) 0.242 720 202 752 × 2 = 0 + 0.485 440 405 504;
  • 29) 0.485 440 405 504 × 2 = 0 + 0.970 880 811 008;
  • 30) 0.970 880 811 008 × 2 = 1 + 0.941 761 622 016;
  • 31) 0.941 761 622 016 × 2 = 1 + 0.883 523 244 032;
  • 32) 0.883 523 244 032 × 2 = 1 + 0.767 046 488 064;
  • 33) 0.767 046 488 064 × 2 = 1 + 0.534 092 976 128;
  • 34) 0.534 092 976 128 × 2 = 1 + 0.068 185 952 256;
  • 35) 0.068 185 952 256 × 2 = 0 + 0.136 371 904 512;
  • 36) 0.136 371 904 512 × 2 = 0 + 0.272 743 809 024;
  • 37) 0.272 743 809 024 × 2 = 0 + 0.545 487 618 048;
  • 38) 0.545 487 618 048 × 2 = 1 + 0.090 975 236 096;
  • 39) 0.090 975 236 096 × 2 = 0 + 0.181 950 472 192;
  • 40) 0.181 950 472 192 × 2 = 0 + 0.363 900 944 384;
  • 41) 0.363 900 944 384 × 2 = 0 + 0.727 801 888 768;
  • 42) 0.727 801 888 768 × 2 = 1 + 0.455 603 777 536;
  • 43) 0.455 603 777 536 × 2 = 0 + 0.911 207 555 072;
  • 44) 0.911 207 555 072 × 2 = 1 + 0.822 415 110 144;
  • 45) 0.822 415 110 144 × 2 = 1 + 0.644 830 220 288;
  • 46) 0.644 830 220 288 × 2 = 1 + 0.289 660 440 576;
  • 47) 0.289 660 440 576 × 2 = 0 + 0.579 320 881 152;
  • 48) 0.579 320 881 152 × 2 = 1 + 0.158 641 762 304;
  • 49) 0.158 641 762 304 × 2 = 0 + 0.317 283 524 608;
  • 50) 0.317 283 524 608 × 2 = 0 + 0.634 567 049 216;
  • 51) 0.634 567 049 216 × 2 = 1 + 0.269 134 098 432;
  • 52) 0.269 134 098 432 × 2 = 0 + 0.538 268 196 864;
  • 53) 0.538 268 196 864 × 2 = 1 + 0.076 536 393 728;
  • 54) 0.076 536 393 728 × 2 = 0 + 0.153 072 787 456;
  • 55) 0.153 072 787 456 × 2 = 0 + 0.306 145 574 912;
  • 56) 0.306 145 574 912 × 2 = 0 + 0.612 291 149 824;
  • 57) 0.612 291 149 824 × 2 = 1 + 0.224 582 299 648;
  • 58) 0.224 582 299 648 × 2 = 0 + 0.449 164 599 296;
  • 59) 0.449 164 599 296 × 2 = 0 + 0.898 329 198 592;
  • 60) 0.898 329 198 592 × 2 = 1 + 0.796 658 397 184;
  • 61) 0.796 658 397 184 × 2 = 1 + 0.593 316 794 368;
  • 62) 0.593 316 794 368 × 2 = 1 + 0.186 633 588 736;
  • 63) 0.186 633 588 736 × 2 = 0 + 0.373 267 177 472;
  • 64) 0.373 267 177 472 × 2 = 0 + 0.746 534 354 944;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


5. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.000 282 006 284(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100(2)

6. Positive number before normalization:

0.000 282 006 284(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 282 006 284(10) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100(2) =


0.0000 0000 0001 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100(2) × 20 =


1.0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100(2) × 2-12


8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): -12


Mantissa (not normalized):
1.0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(10)


10. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1011(10) =


011 1111 0011(2)


12. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, only if necessary (not the case here).


Mantissa (normalized) =


1. 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100 =


0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
011 1111 0011


Mantissa (52 bits) =
0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100


Decimal number -0.000 282 006 284 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0100 0111 1100 0100 0101 1101 0010 1000 1001 1100


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100